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Builds Flux manifests locally, diffs YAML files, patches FluxInstance upgrades, creates authentication secrets, traces GitOps delivery pipelines, and bootstraps clusters with the Flux Operator. Use this skill whenever the user mentions flux-operator, FluxInstance, FluxReport, ResourceSet, ResourceSetInputProvider, Flux CD operator management, or asks about GitOps CLI tooling for Kubernetes with Flux. Also trigger when users ask about building Flux manifests, diffing YAML, patching Flux instances, creating Flux secrets, tracing GitOps delivery pipelines, or bootstrapping clusters with Flux. Even if the user just says "flux operator" or "flux-operator cli" without details, this skill has the authoritative reference.

日本語の概要は準備中です。原文の説明を表示しています。

Write customer case studies and success stories using the Situation-Complication-Resolution (SCR) narrative framework and Barbara Minto's Pyramid Principle (conclusion first). Produces case studies where the headline states the result, the complication makes readers recognize their own situation, and every paragraph advances the story. Use when the user asks for a case study, customer story, customer success story, win story, reference write-up, or "turn this customer into a case study". Reads brand voice and service catalog from knowledge/. For a press announcement, see press-release-writer. For pitching the story to media, see pr-pitch-writer. For repurposing it into social, see content-repurposer.

日本語の概要は準備中です。原文の説明を表示しています。

Generates Google Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.

日本語の概要は準備中です。原文の説明を表示しています。

Use when configuring or troubleshooting a Salesforce B2C Commerce (SFCC) storefront — including Business Manager site creation, SFRA cartridge path setup, customer groups, search index rebuilding, and key quota limits. Trigger keywords: SFCC, Commerce Cloud, Business Manager, storefront, cartridge, SFRA, site preferences, replication. NOT for B2B Commerce on Lightning (WebStore, BuyerGroup) — use admin/b2b-commerce-store-setup. NOT for choosing SFCC vs B2B Commerce — use architect/b2b-vs-b2c-architecture.

日本語の概要は準備中です。原文の説明を表示しています。

Auto-activate for polyfactory, ModelFactory, DataclassFactory, MsgspecFactory, AttrsFactory, Use, register_fixture, pytest plugin, __random_seed__, or coverage(). Not for production seeding.

日本語の概要は準備中です。原文の説明を表示しています。

Generates a minimal .editorconfig with sensible defaults for a repository. Use when starting work in a new repository, when a project has no .editorconfig, or when the user asks to add or standardise editor and formatting settings.

日本語の概要は準備中です。原文の説明を表示しています。

S3, multipart uploads, CDN integration, and presigned URLs for file storage. Activate on: file upload, S3, presigned URL, multipart upload, CDN, blob storage, image upload, media storage. NOT for: data warehouse storage (use lakehouse-architect), database design (use dimensional-modeler).

日本語の概要は準備中です。原文の説明を表示しています。

Meta-skill that orchestrates the discourse skill suite: routes between steel-man-argument, socratic-questioning, toulmin-argument-analysis, logical-fallacy-detector, bad-faith-rhetoric-detector, discourse-elision-analyzer, forensic-speech-structure, and productive-discourse-facilitator. Use when analyzing conversations, facilitating discourse, or operating as a dialogue copilot. Maintains mode (silent analysis, coaching overlay, active facilitator) and decides which skills to invoke based on conversation dynamics.

日本語の概要は準備中です。原文の説明を表示しています。

ALIAS for dag-orchestrator. The original DAG execution skill, now unified with orchestrator into dag-orchestrator. Use dag-orchestrator for the full HTDAG experience.

日本語の概要は準備中です。原文の説明を表示しています。

App Store and Google Play submission automator with Fastlane, screenshot automation, metadata management, and TestFlight/internal testing. Activate on: app store submission, Fastlane, TestFlight, Google Play Console, screenshot automation, metadata management, app review, code signing, provisioning profiles. NOT for: CI/CD pipeline setup (use github-actions-pipeline-builder), app architecture (use react-native-architect), analytics (use mobile-analytics-crash-reporting-expert).

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level semiconductor materials covering band theory, silicon processing, compound semiconductors, wide bandgap materials, and semiconductor device fundamentals.

日本語の概要は準備中です。原文の説明を表示しています。

Execute story implementation following a context filled story spec file. Use when the user says "dev this story [story file]" or "implement the next story in the sprint plan"

日本語の概要は準備中です。原文の説明を表示しています。

Fornece orientação para treinamento RL agentico nativo do PyTorch usando torchforge, biblioteca da Meta que separa infraestrutura de algoritmos. Use quando você quer abstrações limpas de RL, fácil experimentação de algoritmos, ou treinamento escalável com Monarch e TorchTitan.

日本語の概要は準備中です。原文の説明を表示しています。

Create or repair a project-local Inspector profile after INSPECTOR_PROFILE_REQUIRED, INSPECTOR_PROFILE_INCOMPLETE, INSPECTOR_PROFILE_INVALID, or PROFILE_AUTHORING_REQUIRED, using Unity component source, custom Inspector evidence, serialized surfaces, and validation diagnostics.

日本語の概要は準備中です。原文の説明を表示しています。

Generates a comprehensive .editorconfig from the project's structure and the user's preferences, so editors format files consistently across languages. Use when a repository has no .editorconfig or its formatting is inconsistent across editors.

日本語の概要は準備中です。原文の説明を表示しています。

Plan, scaffold, implement, and integrate a complete new emulated computer or console in the EMULATORS repository. Use when Codex creates a new machine, platform, hardware model, or emulator executable; decides which existing CPUs, chips, memory, I/O, video, sound, ROM, and framework classes to reuse or extend; or coordinates several emulator subsystems into a bootable tested system.

日本語の概要は準備中です。原文の説明を表示しています。

Create and integrate the machine-level core of a new EMULATORS emulator, including Computer and Emulator derivatives, memory and port maps, chip ownership and wiring, clock coordination, model configuration, commands, formatters, executables, and Visual Studio projects. Use when scaffolding a machine namespace, adding a model or regional variant, assembling existing components into a computer, or making a new emulator build and start.

日本語の概要は準備中です。原文の説明を表示しています。

Activates a structured decorator framework that modifies how Claude reasons, responds, and formats output. Trigger this skill whenever a prompt contains one or more markers prefixed with +++, such as +++Reasoning, +++StepByStep, +++Tone(style=formal), or any other +++ marker, regardless of what follows in the prompt. Also trigger when the user asks to activate, list, or clear decorators, references the prompt decorator framework, or uses phrases like "use decorator", "apply +++", or "what decorators are available". This skill must be active for any +++ marker to take effect.

日本語の概要は準備中です。原文の説明を表示しています。

Deploy and use the Exasol Text AI Extension (TXAIE) with notebook-connector. Covers `deploy_license`, `initialize_text_ai_extension`, the `PYTHON3_TXAIE` language container, the Extraction API classes `StandardExtractor`, `NamedEntityExtractor`, `TopicClassifierExtractor`, `PipelineExtractor`, and `BranchExtractor`, named-entity, zero-shot classification, and feature extraction runs, default-model installation, and result-table querying such as `TXAIE_AUDIT_LOG`.

日本語の概要は準備中です。原文の説明を表示しています。

Set up notebook-connector configuration for Exasol AI workflows through the Secrets Python API. Covers secure config store (`scs`) creation, the `AILabConfig` and `StorageBackend` key sources, backend-specific config values such as `db_host_name`, `db_schema`, `storage_backend`, and `huggingface_token`, Python validation, and handoff to downstream notebook-connector skills.

日本語の概要は準備中です。原文の説明を表示しています。

Run convex-doctor static analysis, interpret findings, and fix issues across security, performance, correctness, schema, and architecture categories. Use when running convex-doctor, fixing convex-doctor warnings or errors, improving the convex-doctor score, or when asked about Convex code quality, static analysis, or linting Convex functions.

日本語の概要は準備中です。原文の説明を表示しています。

Audit Azure Blob and ADLS storage accounts for public access exposure, weak or long-lived SAS tokens, missing encryption at rest, disabled HTTPS-only traffic, and outdated TLS versions using the azure-mgmt-storage Python SDK.

日本語の概要は準備中です。原文の説明を表示しています。

Providerneutrale Operator- und Teamleader-Rolle für komplexe, länger laufende oder planbasierte Vorhaben. Verwenden bei `$operator`, `/operator`, "übernimm als Operator" oder "arbeite den Plan weiter ab", um den nächsten substanziellen Planschritt zu wählen, unabhängige Arbeitspakete kontrolliert zu delegieren und Ergebnisse evidenzbasiert abzunehmen und zu integrieren.

日本語の概要は準備中です。原文の説明を表示しています。

Track independent contractor payments, collect W-9s, determine 1099-NEC filing requirements, and avoid penalties. Covers the $600 threshold (2025) and $2,000 threshold (2026), Jan 31 deadline, corporate exceptions, backup withholding, and penalty schedule ($60–$660/form). Trigger on "1099", "contractor payment", "do I need to file a 1099", "W-9", "independent contractor".

日本語の概要は準備中です。原文の説明を表示しています。